Design, develop, and deploy machine learning models and algorithms to solve complex business problems.
Implement MLOps best practices to ensure robust, scalable, and maintainable machine learning pipelines.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Monitor and optimize the performance of machine learning models in production.
Develop and maintain automated testing, continuous integration, and continuous deployment (CI / CD) pipelines for machine learning models.
Ensure data quality and integrity throughout the machine learning lifecycle.
Stay up-to-date with the latest advancements in machine learning, MLOps, and related technologies.
Qualifications :
4+ years of experience in machine learning and data science.
Proven experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TFX).
Strong programming skills in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
Solid understanding of software engineering principles, including version control (e.g., Git), testing, and code reviews.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
Preferred Qualifications :
Experience with big data technologies (e.g., Hadoop, Spark).
Knowledge of data engineering and ETL processes.
Familiarity with DevOps practices and tools.
ref : hirist.tech)
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Machine Learning Engineer • Bangalore
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